UMMS Affiliation

Eunice Kennedy Shriver Center; Department of Psychiatry

Publication Date

2019-11-13

Document Type

Editorial

Disciplines

Biostatistics | Investigative Techniques | Laboratory and Basic Science Research | Neuroscience and Neurobiology

Abstract

The last decade has seen increasing attention to the problem of scientific reproducibility, across a broad range of scientific fields (Camerer et al., 2016;Morrison, 2014;Open Science Collaboration, 2015). Within the field of neuroimaging, there has been a particular focus on issues of analytic variability (Bowring et al., 2019;Carp, 2012) statistical power (Button et al., 2013;Poldrack et al., 2017), and test-retest reliability (Bennett and Miller, 2013), all of which have raised alarms regarding the potential for irreproducible results. In addition, failed replications (Boekel et al., 2015;Dinga et al., 2019) and meta-analytic null results (Müller et al., 2017) have raised particular concern about studies of group and individual differences. This special issue was developed in light of these emerging concerns, with the goal of highlighting and encouraging work that aims to both quantify and improve the reproducibility of neuroimaging research. Here we provide a brief overview of the papers within this special issue.

Keywords

neuroimaging research, scientific reproducibility

Rights and Permissions

© 2019 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

DOI of Published Version

10.1016/j.neuroimage.2019.116357

Source

Neuroimage. 2019 Nov 13:116357. doi: 10.1016/j.neuroimage.2019.116357. [Epub ahead of print] Link to article on publisher's site

Journal/Book/Conference Title

NeuroImage

Related Resources

Link to Article in PubMed

PubMed ID

31733374

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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